package imgscala;

import com.google.common.base.Charsets;
import com.google.common.io.Files;

import java.awt.Graphics2D;
import java.awt.color.ColorSpace;
import java.awt.image.BufferedImage;
import java.awt.image.ColorConvertOp;
import java.io.*;
import java.net.MalformedURLException;
import java.net.URL;
import java.util.ArrayList;
import java.util.List;
import java.util.concurrent.Callable;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.LinkedBlockingQueue;
import java.util.concurrent.atomic.AtomicInteger;

import javax.imageio.ImageIO;

/*
* pHash-like image hash. 
* Author: Elliot Shepherd (elliot@jarofworms.com
* Based On: http://www.hackerfactor.com/blog/index.php?/archives/432-Looks-Like-It.html
*/
public class ImagePHash {

    private static int size = 32;
    private static int smallerSize = 8;
    static private double[] c;
    static {
        c = new double[size];
        for (int i = 1; i < size; i++) {
            c[i] = 1;
        }
        c[0] = 1 / Math.sqrt(2.0);
    }

    public static int distance(String s1, String s2) {
        int counter = 0;
        for (int k = 0; k < s1.length(); k++) {
            if (s1.charAt(k) != s2.charAt(k)) {
                counter++;
            }
        }
        return counter;
    }

    // Returns a 'binary string' (like. 001010111011100010) which is easy to do a hamming distance on.
    public static String getHash(BufferedImage img) throws Exception {

       
       /* 1. Reduce size. 
        * Like Average Hash, pHash starts with a small image. 
        * However, the image is larger than 8x8; 32x32 is a good size. 
        * This is really done to simplify the DCT computation and not 
        * because it is needed to reduce the high frequencies.
        */
        img = resize(img, size, size);
       
       /* 2. Reduce color. 
        * The image is reduced to a grayscale just to further simplify 
        * the number of computations.
        */
        img = grayscale(img);

        double[][] vals = new double[size][size];

        for (int x = 0; x < img.getWidth(); x++) {
            for (int y = 0; y < img.getHeight(); y++) {
                vals[x][y] = getBlue(img, x, y);
            }
        }
       
       /* 3. Compute the DCT. 
        * The DCT separates the image into a collection of frequencies 
        * and scalars. While JPEG uses an 8x8 DCT, this algorithm uses 
        * a 32x32 DCT.
        */
        double[][] dctVals = applyDCT(vals);
        //System.out.println("DCT: " + (System.currentTimeMillis() - start));
       
       /* 4. Reduce the DCT. 
        * This is the magic step. While the DCT is 32x32, just keep the 
        * top-left 8x8. Those represent the lowest frequencies in the 
        * picture.
        */
       /* 5. Compute the average value. 
        * Like the Average Hash, compute the mean DCT value (using only 
        * the 8x8 DCT low-frequency values and excluding the first term 
        * since the DC coefficient can be significantly different from 
        * the other values and will throw off the average).
        */
        double total = 0;

        for (int x = 0; x < smallerSize; x++) {
            for (int y = 0; y < smallerSize; y++) {
                total += dctVals[x][y];
            }
        }
        total -= dctVals[0][0];

        double avg = total / (double) ((smallerSize * smallerSize) - 1);
   
       /* 6. Further reduce the DCT. 
        * This is the magic step. Set the 64 hash bits to 0 or 1 
        * depending on whether each of the 64 DCT values is above or 
        * below the average value. The result doesn't tell us the 
        * actual low frequencies; it just tells us the very-rough 
        * relative scale of the frequencies to the mean. The result 
        * will not vary as long as the overall structure of the image 
        * remains the same; this can survive gamma and color histogram 
        * adjustments without a problem.
        */
        String hash = "";

        for (int x = 0; x < smallerSize; x++) {
            for (int y = 0; y < smallerSize; y++) {
                if (x != 0 && y != 0) {
                    hash += (dctVals[x][y] > avg ? "1" : "0");
                }
            }
        }

        return hash;
    }

    private static BufferedImage resize(BufferedImage image, int width, int height) {
        BufferedImage resizedImage = new BufferedImage(width, height, BufferedImage.TYPE_INT_ARGB);
        Graphics2D g = resizedImage.createGraphics();
        g.drawImage(image, 0, 0, width, height, null);
        g.dispose();
        return resizedImage;
    }


    private static BufferedImage grayscale(BufferedImage img) {
        ColorConvertOp colorConvert = new ColorConvertOp(ColorSpace.getInstance(ColorSpace.CS_GRAY), null);
        colorConvert.filter(img, img);
        return img;
    }

    private static int getBlue(BufferedImage img, int x, int y) {
        return (img.getRGB(x, y)) & 0xff;
    }

    // DCT function stolen from http://stackoverflow.com/questions/4240490/problems-with-dct-and-idct-algorithm-in-java



    private static double[][] applyDCT(double[][] f) {
        int N = size;

        double[][] F = new double[N][N];
        for (int u = 0; u < N; u++) {
            for (int v = 0; v < N; v++) {
                double sum = 0.0;
                for (int i = 0; i < N; i++) {
                    for (int j = 0; j < N; j++) {
                        sum += Math.cos(((2 * i + 1) / (2.0 * N)) * u * Math.PI) * Math.cos(((2 * j + 1) / (2.0 * N)) * v * Math.PI) * (f[i][j]);
                    }
                }
                sum *= ((c[u] * c[v]) / 4.0);
                F[u][v] = sum;
            }
        }
        return F;
    }

    public static void main(String[] args) throws IOException {
        List<String> urls = Files.readLines(new File("image.csv"), Charsets.UTF_8);
        ExecutorService exec = Executors.newFixedThreadPool(64);
        for (String u : urls) {
            exec.submit(new GetHashTask(u));
        }
    }

}


class GetHashTask implements Callable<String> {
    static AtomicInteger count = new AtomicInteger(0);
    private String url;
    ImagePHash p;

    public GetHashTask(String url) {
        this.url = url;
        p = new ImagePHash();
    }

    @Override
    public String call() throws Exception {
        BufferedImage bi = ImageIO.read(new URL(url));
        String hash = p.getHash(bi);
        System.out.println(count.incrementAndGet() + "," + url + "," + hash);
        return hash;
    }
}